Robust feature detection for facial expression recognition

Ioannou, S; Caridakis, G; Karpouzis, K; Kollias, S

dc.contributor.author	Ioannou, S	en
dc.contributor.author	Caridakis, G	en
dc.contributor.author	Karpouzis, K	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:27:07Z
dc.date.available	2014-03-01T01:27:07Z
dc.date.issued	2007	en
dc.identifier.issn	1687-5176	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/18332
dc.subject	Facial Expression Recognition	en
dc.subject	Feature Detection	en
dc.subject.other	IMAGE SEGMENTATION	en
dc.subject.other	MOTION ESTIMATION	en
dc.subject.other	OPTICAL-FLOW	en
dc.subject.other	FACE	en
dc.subject.other	MODELS	en
dc.subject.other	CLASSIFICATION	en
dc.subject.other	ALGORITHMS	en
dc.subject.other	EXTRACTION	en
dc.subject.other	NETWORKS	en
dc.subject.other	MPEG-4	en
dc.title	Robust feature detection for facial expression recognition	en
heal.type	journalArticle	en
heal.identifier.primary	10.1155/2007/29081	en
heal.identifier.secondary	29081	en
heal.identifier.secondary	http://dx.doi.org/10.1155/2007/29081	en
heal.language	English	en
heal.publicationDate	2007	en
heal.abstract	This paper presents a robust and adaptable facial feature extraction system used for facial expression recognition in human-computer interaction (HCI) environments. Such environments are usually uncontrolled in terms of lighting and color quality, as well as human expressivity and movement; as a result, using a single feature extraction technique may fail in some parts of a video sequence, while performing well in others. The proposed system is based on a multicue feature extraction and fusion technique, which provides MPEG-4-compatible features assorted with a confidence measure. This confidence measure is used to pinpoint cases where detection of individual features may be wrong and reduce their contribution to the training phase or their importance in deducing the observed facial expression, while the fusion process ensures that the final result regarding the features will be based on the extraction technique that performed better given the particular lighting or color conditions. Real data and results are presented, involving both extreme and intermediate expression/emotional states, obtained within the sensitive artificial listener HCI environment that was generated in the framework of related European projects. Copyright (C) 2007 Spiros Ioannou et al.	en
heal.publisher	HINDAWI PUBLISHING CORPORATION	en
heal.journalName	Eurasip Journal on Image and Video Processing	en
dc.identifier.doi	10.1155/2007/29081	en
dc.identifier.isi	ISI:000207756800001	en
dc.identifier.volume	2007	en